Wednesday, June 8, 2016

In 2005, Washington Post journalist Robert
O’Harrow published a popular book on mass data-mining entitled, No Place to Hide. He identified new ways both industry and
government collect vast amounts of personal information on Americans by working
separately and also in collaboration.The “War on Terror” had accentuated a data-driven surveillance society. The
book received widespread notice. The conservative columnist William Safire
wrote in the New York Times: “The
computer's ability to collect an infinity of data about individuals -- tracking
every movement and purchase, assembling facts and traits in a personal dossier,
forgetting nothing -- was in place before 9/11. But among the unremarked
casualties of that day was a value that Americans once treasured: personal
privacy.”The idea that individuals
could retain a sphere that is ''nobody's business'' rapidly had disintegrated.A new “big business of everybody's business” had
become the order of the day.

Meanwhile, liberal law professor
Geoffrey R. Stone, after reading O’Harrow, raised an existential question. “Once
we understand that our every move is being tracked, monitored, recorded and
collated, will we retain our essential sense of individual autonomy and personal
dignity?” Where do people retreat if there is no place to hide? There also are serious risks inherent in the
construction of new data-based dossiers: data error; stolen data; and unintended
public data disclosure.Finally, as
Stone notes, government may use its data collection capability “to suppress
dissent and impose conformity.”Despite official
claims that data-mining promotes security, “history teaches that once
government has such information, it will inevitably use it to harass and
silence those who question its policies.”

To be sure, O’Harrow was not the
first writer to tackle this important subject matter.Almost a decade earlier, academic specialists
David Lyon and Elia Zureik edited an important book, Computers, Surveillance, and Privacy (1996), in which they had
identified the new issue of “dataveillance.” For example, one of the authors in
that volume, Colin J. Bennett, wrote:

Mass
dataveillance begins with no a priori knowledge of the individual(s) who may
warrant attention. Its aim is to screen groups of people with a view to
finding those worth subjecting to
personal dataveillance. It is based on a general rather than specific suspicion,
but also tries to deter or constrain behavior. All forms of computer matching
are mass dataveillance techniques. They all involve the aggregate comparison of
different data systems to identify those ‘hits’ that prima facie warrant
further investigation.

Today,
mass data-mining affects more Americans than ever before. This is so because electronic records widely have
displaced paper records and electronic communications now are prevalent in many
spheres of both our personal and public lives.More than 90 percent of Americans use cell phones.The Internet has spread across the landscape transcending
boundaries of race, gender, and class. In 2013, more than 85 percent of the nation’s
population regularly went online. More
than half of the entire American adult population uses online social networking
sites. U.S. authorities also ask online
service companies for account information on thousands of individuals. To some extent, the idea that too much data
now exists to make sense of it is relevant.The common concern -- “drowning in data but starving for knowledge” —poses
challenges for government data-mining, but the official development of more
efficient systems for record matching and sorting promises to keep pace with
the explosion of information.

Of course, not all data-mining is
nefarious. It can be an effective tool for scientists and other researchers,
who refer to it as “knowledge extraction” and
“information harvesting.” It builds knowledge from large sets of data by
identifying patterns; it makes generalizations about future behavior based on past
behavior.Data-mining can be used for “pattern
detection” to identify small departures from the norm, or unusual
patterns.As information analyst Joyce
Jackson notes, “Data mining allows the automated discovery of implicit patterns
and interesting knowledge that’s hiding in large amounts of data.”

But while data-mining
proves useful in some fields, its application to the “War on Terror” at best is
dubious. There is no way that patterns discerned from data analysis can predict
political violence.What may appear to
be “suspicious” behaviors or patterns likely are anomalies – an oddity or
peculiarity with little discernible meaning.Using anomalies to create a suspect list is deeply flawed.As Jim Harper of the Cato Institute concludes:

First, terrorist acts and their
precursors are too rare in our society for there to be patterns to find. There
simply is no nugget of information to mine.

Second, the lack of suitable
patterns means that any algorithm used to turn up supposedly suspicious behavior
or suspicious people will yield so many false positives as to make it useless.
A list of potential terror suspects generated from pattern analysis would not
be sufficiently targeted to justify investigating people on the list.

A major
study conducted by the National Research Council confirms this analysis.The report, ironically funded by the U.S.
Department of Homeland Security, offers a blistering attack on the
effectiveness of data-mining for terrorism discovery. “Automated identification
of terrorists through data mining (or any other known methodology) is neither
feasible as an objective nor desirable as a goal of technology development
efforts," the report found. "Even in well-managed programs, such
tools are likely to return significant rates of false positives, especially if
the tools are highly automated." A false positive -- that is, erroneously
identifying someone as a terrorist suspect -- can have disastrous consequences
for individuals.It can lead to major
privacy intrusions, as well as targeted surveillance and harassment in everyday
life if security agencies decide to “neutralize” subjects. False positives can
lead to individuals “being in trouble with the government” for no legitimate
reason.

So the ability of government to sort
through mass data to discover preparation and planning for terrorism is a waste
of resources. By contrast, data-mining is very effective to identify people and
groups involved in dissident politics.Both
the FBI and NSA can sort through billions of records to find patterns of
expression critical of government. Once the FBI locates subjects to neutralize,
they can use data-mining directed at specific individuals to maximize their
intelligence operations. The National
Research Council reports:

"Once an individual is under strong suspicion of participating in some kind of terrorist activity, it is standard practice to examine that individual’s financial dealings, social networks, and comings and goings to identify coconspirators, for direct surveillance, etc. Data mining can expedite much of this by providing such information as (1) the names of individuals who have been in e‑mail and telephone contact with the person of interest in some recent time period, (2) alternate residences, (3) an individual’s financial withdrawals and deposits, (4) people that have had financial dealings with that individual, and (5) recent places of travel."

About Me

I am a former college teacher who now devotes his full time to writing and the visual arts. My book, "The Dangers of Dissent: The FBI and Civil Liberties since 1965," was published by Rowman and Littlefield/Lexington Books (October 2010). A second volume, "Surveillance in America: Critical Analysis of the FBI, 1920 to the Present," was published by Lexington Books in June 2012. I live in Silver Spring, MD.